Everything a user sees when they open Pinterest is chosen and ranked by AI. The system — called Pinnability — predicts how likely each individual user is to engage with each Pin and orders content accordingly. No human editor curates the home feed. The system has been continuously updated since 2015; the most recent major version, TransActV2, launched in 2025 and personalizes results using more than 16,000 historical user actions per person.

The system operates in two stages. First, a retrieval layer uses over 20 candidate generators — including embedding-based nearest-neighbor search across billions of Pins — to assemble a pool of potentially relevant content for each user. Then a ranking layer uses deep neural networks to score each candidate using combinations of Pin signals, long-term user preference embeddings (mathematical representations of a user's tastes built from their entire save history), and real-time signals reflecting what the user has done in the current session. TransActV2 extended the historical action window from 100 to 16,000 actions per user, running on custom GPU kernels to maintain response times under 100 milliseconds.